Rule-Based Data Cleansing
A cleansing approach that improves data quality through explicit business rules and validation conditions.
Rule-based data cleansing focuses on correcting data issues through defined logic and business rules rather than through statistical guessing. Examples include rules such as an order date cannot be later than a delivery date, or a country code must belong to an approved dictionary. This approach is especially valuable in enterprise data environments because it provides explainable and auditable quality control. However, if rules are not managed properly, maintenance cost rises and the system becomes brittle. For that reason, rule governance matters as much as rule execution.
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